First round was a simple NLP case about output rating. Second round was a coding problem. Coding itself was not hard, but they will ask some statistics questions to you to prove the correctness of your code. Third round was a panel interview primarily to talk about your experience. They might also ask you to explain ML term to business people. The last round was a total mess, they send out very loose guidelines and case scenario prior to the interview, and I prepared for a complete wrong direction.
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ML practical questions in terms of data collection
Difference between linear and logarithmic regression and all the questions were related to projects
What are your biggest weaknesses/strengths?
- What is the maximum sum of values in a list without using any adjacent values? - Given a 2D matrix of 1's and 0's, identify the number of islands present, where an island is a group 1's surrounded on all sides by either the matrix edge or 0's, while diagonal touching counts as a separate island
Talk about the projects that you have implemented.
It was a behavioural based interview
What is decision tree and what is entropy?
Tell me about yourself. What interests you about this position? What do you know about our company? What are your greatest professional strengths? Can you describe a challenge you've overcome and how you dealt with it? Where do you see yourself in five years? Why do you want to leave your current job? What is your greatest professional achievement? Tell me about a time you worked effectively under pressure. What is your management style? How do you handle conflicts in the workplace? Describe a situation when you had to meet a tight deadline. What motivates you? Why should we hire you? Do you have any questions for us?
- CNN classifier with a messy db of images - Logic questions - CSV manipulations
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